Dept of Environmental Science, Policy, and Management

I work on problems in ecological forecasting and decision making under
uncertainty, with applications for global change, conservation and
natural resource management. I am particularly interested in how we can
predict or manage ecological systems that may experience regime shifts:
sudden and dramatic changes that challenge both our models and available
data. The rapid expansion in both computational power and the available
ecological and environmental data enables and requires new mathematical,
statistical and computational approaches to these questions. Ecology
has much to learn about what are and are not useful from advances in
informatics & computer science, just as it has from statistics and
mathematics. Traditional approaches to ecological modeling and resource
management such as stochastic dynamic systems, Bayesian inference, and
optimal control theory must be adapted both to take advantage of all
available data while also dealing with its imperfections. My approach
blends ecological theory with the synthesis of heterogeneous data and
the development of software -- a combination now recognized as data
science.

I am co-founder of the rOpenSci project, a senior fellow at
BIDS, and a science adviser to
NCEAS, reflecting my interests in
open science, data science, and ecoinformatics.